Abstract (Official) DESCRIPTION (provided by applicant): The relationship between the behavioral deficits and anatomical damage produced by a stroke is only partial, since physiological dsyfunction can be measured in brain regions far removed from the lesion. These non-local physiological deficits can be assessed using functional connectivity magnetic resonance imaging (fcMRl), which measures the temporal correlation between brain regions in the blood-oxygenation-level-dependent (BOLD) signal. Studies of fcMRl in healthy adults have identified distributed brain networks that underlie different behavioral functions, such as attention, motor control, and language. Our previous work on stroke patients with spatial neglect has shown that fcMRl deficits within the attention network correlate with a patient's deficit in the neglected field. This grant proposes that fcMRl can be used more broadly to understand the deficits produced by stroke across behavioral domains. We will measure fcMRl in a large, heterogeneous sample of stroke patients, and test several hypotheses of how strokes produce dysfunction in brain networks and how this dysfunction correlates with behavioral deficits. We predict that decreases in inter-hemispheric connectivity in motor and attention networks, which are bilaterally organized, will correlate with corresponding behavioral deficits and that these correlations will show functional specificity. For example, connectivity within an arm-defined motor network will predict upper-extremity function better than lower-extremity function. We determine the correlation between connectivity and behavior in an asymmetrically organized network, language, and compare the importance of inter-hemispheric vs intra-hemispheric connectivity. We examine how the functioning of multiple brain networks interact to produce a single behavioral deficit, and hypothesize that the connectivity of some networks, such as attention, correlates with behavior across domains. We measure fcMRl longtitudinally to determine if connectivity recovers in different networks at different rates and whether that recovery correlates with behavioral recovery. Finally, we study how changes in connectivity produced by a stroke depend on the type of tracts that are structurally damaged.